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Integrated patient care

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Title: Integrated patient care.
Abstract: A therapy regimen, e.g., a contingent medication prescription, may be created and automatically distributed to a patient via an integrated patient care system. A clinician may create therapy instructions by at least associating patient conditions with one or more therapy regimens, e.g., medication prescriptions. In some examples, the integrated patient care system may present historical condition data to the clinician to aid the clinician with creating and/or updating the therapy instructions specific to the patient. A therapy module of the integrated patient care system may use the therapy instructions to automatically select a therapy regimen from the therapy instructions based on a patient condition detected based on a sensed physiological parameter. The physiological parameter of the patient may be sensed by an implanted or external sensor. In some examples, the therapy regimen can be presented to the patient according to a predetermined schedule or in response to the detected condition. ...


Medtronic, Inc. - Browse recent Medtronic patents - Minneapolis, MN, US
Inventors: Tommy D. Bennett, Yong Kyun Cho, Randolph M. Biallas
USPTO Applicaton #: #20120108984 - Class: 600485 (USPTO) - 05/03/12 - Class 600 
Surgery > Diagnostic Testing >Cardiovascular >Measuring Pressure In Heart Or Blood Vessel



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The Patent Description & Claims data below is from USPTO Patent Application 20120108984, Integrated patient care.

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TECHNICAL FIELD

The disclosure relates to monitoring and treating a patient's medical condition.

BACKGROUND

Some medical conditions may require frequent monitoring and adjustment of treatment regimens. For example, the severity of and/or symptoms associated with a particular medical condition may have a propensity to change over time. Clinicians or other healthcare professionals may frequently monitor the patient's condition and adjust one or more treatment regimens when needed to effectively manage the medical condition.

SUMMARY

In general, this disclosure is directed to an integrated patient care system and techniques performed by the integrated patient care system for monitoring and treating a medical condition of a patient. A therapy regimen, e.g., a contingent medication prescription, may be created and automatically distributed to a patient via the integrated patient care system. The system may allow a clinician to create therapy instructions that associate patient conditions with one or more therapy regimens, e.g., contingent medication prescriptions. The system may provide historical condition data to the clinician to facilitate the creation or updating of the therapy instructions. Once the therapy instructions are created, a therapy module, e.g., an external computing device, may automatically select a therapy regimen from a plurality of therapy regimens for delivery to the patient based on a patient condition detected based on a physiological parameter sensed by one or more sensors. The sensor may be an implanted or external sensor that senses at least one physiological parameter, e.g., pulmonary artery pressure or trans-thoracic impedance. After the therapy regimen is selected, the system may present the therapy regimen to the patient, e.g., according to a predetermined schedule, in response to the detected condition, or at the request of the patient.

In one example, the disclosure is directed to a system that includes a clinician module configured to receive input that defines one or more therapy instructions specific to a patient, a sensor configured to sense a physiological parameter indicative of one or more conditions of the patient, and a processor configured to automatically select a therapy regimen from a plurality of stored therapy regimens based on the one or more conditions indicated by the sensed physiological parameter and the one or more therapy instructions. The system also includes a patient display configured to present the selected therapy regimen to the patient.

In another example, the disclosure is directed to a method that includes receiving input from a clinician at a clinician module, wherein the input defines one or more therapy instructions specific to a patient, and sensing a physiological parameter indicative of one or more conditions of the patient with a sensor. The method also includes, with a processor, automatically selecting a therapy regimen from a plurality of stored therapy regimens based on the one or more conditions indicated by the sensed physiological parameter and the one or more therapy instructions, and presenting the selected therapy regimen to the patient via a patient display.

In another example, the disclosure is directed to a system that includes means for receiving input from a clinician that defines one or more therapy instructions specific to a patient, means for sensing a physiological parameter indicative of one or more conditions of the patient, and means for automatically selecting a therapy regimen from a plurality of stored therapy regimens based on the one or more conditions indicated by the sensed physiological parameter and the one or more therapy instructions. The system also includes means for presenting the selected therapy regimen to the patient.

In another aspect, the disclosure is directed to an article of manufacture comprising a computer-readable storage medium. The computer-readable storage medium comprises computer-readable instructions for execution by a processor. The instructions cause a programmable processor to perform any part of the techniques described herein. The instructions may be, for example, software instructions, such as those used to define a software or computer program. The computer-readable medium may be a computer-readable storage medium such as a storage device (e.g., a disk drive, or an optical drive), memory (e.g., a Flash memory, read only memory (ROM), or random access memory (RAM)) or any other type of volatile or non-volatile memory that stores instructions (e.g., in the form of a computer program or other executable) to cause a programmable processor to perform the techniques described herein. The computer-readable medium may be nontransitory.

The details of one or more examples are set forth in the accompanying drawings and the description below. Other features, objects, and advantages will be apparent from the description and drawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a conceptual diagram of an integrated patient care system for monitoring and treating a disorder of a patient.

FIG. 2 is a conceptual diagram of an integrated patient care system for monitoring and treating congestive heart failure of a patient.

FIG. 3 is a conceptual diagram illustrating an implanted sensor for sensing a condition of a patient.

FIG. 4 is a flow diagram illustrating an example technique for receiving therapy instructions from a clinician.

FIG. 5 is a flow diagram illustrating an example technique for displaying historical condition data and receiving therapy instructions from a clinician.

FIG. 6 is a conceptual diagram illustrating an example screen that may display historical condition data and receive therapy instructions from a clinician in the form of the pressure range check instruction.

FIG. 7 is a conceptual diagram illustrating an example screen that may receive therapy instructions specifying contingent prescriptions from a clinician.

FIG. 8 is a flow diagram illustrating an example technique for selecting a therapy regimen from therapy instructions based on a detected patient condition.

FIG. 9 is a flow diagram illustrating an example technique for selecting and transmitting a therapy regimen to a patient, where the therapy regimen is configured to treat congestive heart failure.

FIG. 10 is a flow diagram illustrating an example technique for detecting and transmitting a detected condition to the therapy module.

FIG. 11 is a flow diagram illustrating an example technique performed by the patient module illustrated in FIG. 2 for generating and transmitting patient conditions detected from ancillary and pulmonary artery pressures.

FIG. 12 is a flow diagram illustrating an example technique for displaying a therapy regimen to a patient and receiving feedback regarding the therapy regimen.

FIG. 13 is a flow diagram illustrating an example technique for displaying a selected therapy regimen to a patient and receiving questionnaire answers from the patient.

FIGS. 14A-14E are conceptual diagrams illustrating example screens presenting various therapy regimens based on detected patient conditions.

FIG. 15 is an example display that illustrates information related to the condition of several patients cared for by a single clinic.

FIG. 16 is an example display that illustrates information related to condition data from one patient.

FIG. 17 is an example display that illustrates information related to detecting a patient condition based on a pressure change detection.

FIG. 18 is an example display that illustrates information related to detecting a patient condition based on a pressure range check.

FIG. 19 is an example display that illustrates feedback from a patient related to a distributed therapy regimen.

FIGS. 20-21 are conceptual diagrams illustrating example screens that may be displayed to receive therapy instructions specifying contingent prescriptions from a clinician.

DETAILED DESCRIPTION

Patients may suffer from medical disorders for which frequent monitoring and treatment modifications may be desirable. The degree or severity of the medical condition may have a propensity to change over time, or the patient may unpredictably exhibit new symptoms. Frequent monitoring and treatment modifications may help to more effectively reduce the severity of the medical condition and/or alleviate symptoms associated with the medical condition, or, in some examples, the frequent monitoring and treatment modifications may help to anticipate and prevent progression of the medical condition.

In one example, congestive heart failure (HF) may be such a medical condition requiring frequency monitoring and/or updates to therapy. Patients afflicted with HF may require daily monitoring to avoid transitioning into acute decompensated heart failure, or decompensation. Decompensation generally refers to exacerbated heart failure and can be characterized by certain signs and symptoms, e.g., shortness of breath and weakness, that may require urgent therapy or hospitalization. In some examples, decompensation may be induced by an intercurrent illness (e.g., pneumonia), myocardial infarction, one or more cardiac arrhythmias, uncontrolled hypertension, or failure of the patient to maintain a fluid restriction, diet, or medication regimen.

Although frequent monitoring by a clinician or other healthcare professional may be desirable, this demanding contact may be prohibitively inconvenient, time-consuming, and expensive for both the patient and the clinician. The systems and techniques described herein facilitate monitoring of one or more medical conditions in a manner that may be less expensive, less time-consuming, and more convenient for both the patient and the clinician compared to systems and techniques that require the patient to be physically present at the clinician's office or for the clinician to be physically present with the patient. For example, using the systems and techniques described herein, the clinician may set up therapy instructions that define associations, or relationships, between certain patient conditions and specific therapy regimens. In this manner, the clinician may set up contingent medication prescriptions that are individually prescribed only when called for by a detected patient condition. A sensor at the patient (e.g., implanted in the patient or external to and proximate the patient) senses a physiological parameter of the patient. An external computing device, e.g., a therapy module, may detect a condition of the patient based on an output from the sensor (e.g., the signal indicative of the physiological parameter).

Based on the detected condition, the external computing device automatically selects one of the therapy regimens and distributes or transmits the therapy regimen to the patient. In some examples, the patient may view the therapy regimen displayed on a patient display and take the appropriate action to modify treatment. For example, the patient may read the therapy regimen, and, in response, manually take the contingent medication prescription. In other examples, the system may include a delivery device (e.g., a pill dispenser) that automatically dispenses the prescribed medication to the patient according to the therapy regimen. In some examples, the patient may provide feedback regarding the therapy regimen, e.g., when the therapy was completed, a change in the condition, or any side effects, to the patient interface. This feedback may then be transmitted to the clinician for therapy review.

Although this disclosure generally describes an integrated monitoring system configured to monitor HF, the system may be configured to monitor other patient ailments, diseases or a combination of ailments, diseases and associated symptoms. In any case, the system may detect many patient conditions with one or more sensors and automatically select the appropriate therapy regimen.

FIG. 1 is a schematic illustration of integrated patient care system 10 for monitoring and treating a medical condition of patient 12. System 10 includes patient module 14, clinician module 16, therapy module 18, and network 20. Patient module 14, clinician module 16, and therapy module 18 are configured to communicate with one another via network 20. Although patient module 14, clinician module 16, and therapy module 18 may each be a different device or group of devices, one device may include two or more of the modules. For example, an external computing device with patient 12 may include patient module 14 and therapy module 18 and not require network 20 for communication with each other.

Patient module 14 includes any components necessary for integrating patient 12 into integrated patient care system 10. In the example illustrated in FIG. 1, patient module 14 includes sensor 22, which is configured to sense one or more physiological parameters of patient 12. Using the sensed physiological parameters, sensor 22 may sense one or more conditions of patient 12. Patient module 14 additionally includes patient interface 24 for interaction with patient 12, e.g., for presenting therapy regimens deliverable to patient 12, and/or receiving input from patient 12 (e.g., patient feedback). In addition, in the example illustrated in FIG. 1, patient 12 is schematically illustrated as part of patient module 14 to demonstrate that patient module 14 is associated with patient 12.

In some examples, patient module 14 may also include a processor for performing the techniques attributed to patient module 14 herein. In some examples, a processor may be included within a multi-function device or patient module 14. For example, patient module 14 may include a handheld computing device (e.g., programmer 72 illustrated in FIG. 2), a workstation computer, a personal digital assistant (PDA), a notebook computer, a tablet computer, or another personal computer or other electronic device, any of which may include the processor for performing the techniques attributed to patient module 14. In general, components described as processors of system 10 within this disclosure may each comprise one or more processors, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), programmable logic circuitry, or the like, either alone or in any suitable combination.

In some examples, patient module 14 may also include a memory for storing data. For example, in some examples, the memory may store data related to patient 12, e.g., health information of patient 12 or information identifying patient 12, physiological parameters sensed by sensor 22, detected conditions of patient 12, or any other information related to the medical condition of patient 12. The memory can include any suitable type of memory, such as random access memory (RAM), read only memory (ROM), programmable read only memory (PROM), erasable programmable read only memory (EPROM), electronically erasable programmable read only memory (EEPROM), flash memory, a hard disk, a CD-ROM, a floppy disk, a cassette, magnetic media, optical media, or other computer readable media.

Sensor 22 of patient module 14 may be any sensor configured to sense a physiological parameter of patient 12 useful for detecting a condition of patient 12 related to the patient's medical condition. In other words, the physiological parameter sensed by sensor 22 may be a specific value or signal generated from sensor 22, and a processor of patient module 14 may use this value or signal to detect conditions of the patient. As one example, sensor 22 may be a pressure sensor that senses a pressure value of patient 12, and a processor may detect a specific patient condition based on the pressure value, e.g., when the pressure value falls within a pressure range corresponding to the specific condition. Example types of sensor 22 may include a pressure sensor, a motion sensor (e.g., an accelerometer, gyroscope or pressure transducer), a temperature sensor (e.g., a thermometer), an acoustic sensor, or an impedance sensor. The type of sensor 22 may be selected based on the type of information required to detect and monitor the condition of patient 12. In one example, as described in further detail below with respect to FIGS. 2 and 3, sensor 22 may be a pressure sensor that is implanted within the right ventricle of the heart of patient 12 to sense pressure within the right ventricle indicative of patient 12 HF. In the examples described herein, sensor 22 is implanted within patient 12. However, in other examples, sensor 22 may be external to patient 12, e.g., an ultrasound sensor, one or more surface electrodes, or an activity sensor (also referred to as a motion sensor).

Patient interface 24 may be any user interface suitable for interaction with patient 12. For example, patient interface 24 may include a display and one or more input mechanisms (e.g., buttons or a touch screen display) that allow another component of system 10 to receive input from patient 12. The display may be a liquid crystal display (LCD), dot matrix display, organic light-emitting diode (OLED) display, touch screen, or any other device capable of delivering and/or accepting information. For visible indications of information, a display screen may suffice. For audible and/or tactile indications of information, patient interface 24 may further include one or more audio speakers, voice synthesizer chips, piezoelectric buzzers, or the like. Further, in some examples, patient interface 24 may include a printer configured to print out a distributed therapy regimen. Patient 12 may take the therapy regimen print-out away from patient module 14 as a reminder of the therapy regimen.

Input buttons for patient interface 24 may include a touch pad, increase and decrease buttons, emergency shut off button, and other buttons that may control a treatment delivered to patient 12. A processor of system 10 may control patient interface 24, retrieve data stored in a memory of system 10, store data within a memory of system 10, and/or transmit data from patient module 14 to another module of system 10.

In some examples, patient module 14 may include a delivery device that dispenses medication to patient 12 according to the therapy regimen received from therapy module 18. For example, the delivery device may be a pill dispenser in communication with the processor of patient module 14. Upon receiving the therapy regimen, the pill dispenser may dispense the appropriate medication type and dose at the specified time according to the therapy regimen. In this manner, a delivery device may be loaded with multiple medications that may eventually be prescribed by the therapy regimen. The delivery device may obviate the need for patient 12 to manually retrieve the appropriate medication from various bottles or select the appropriate dose. This can be useful, for example, if patient 12 has difficulty manually obtaining the correct medication in the correct dosage. In another example, the delivery device may be an intravenous drug delivery device. The therapy regimen may include control the rate at which drug is delivered to patient 12, such upon selecting a therapy regimen, patient module 14 may automatically adjust a rate at which a drug is delivered to patient 12 via the intravenous drug delivery device. The drug delivery device may not be intravenous in other examples.

Clinician module 16 may include any components necessary for integrating clinician 15 into integrated patient care system 10. In the example illustrated in FIG. 1, clinician module 16 includes clinician interface 26, which allows clinician 15 to communicate and exchange information with patient module 14 and therapy module 18 of system 10. Clinician 15 is schematically illustrated as part of clinician module 16 to demonstrate that clinician module 16 is associated with clinician 15. In some examples, clinician module 16 may also include a processor for performing the techniques attributed to clinician module 16 herein. In some examples, the processor may be included within a multi-function device of clinician module 16. For example, clinician module 16 may include a handheld computing device, a larger workstation computer, a PDA, a notebook computer, a tablet computer, or another multipurpose personal computer or dedicated computing device, any of which may include the processor for performing the techniques of clinician module 16. Although clinician interface 26 may be a user interface on a single device, clinician interface 26 may be accessible on a variety of devices as needed by clinician 15. For example, clinician 15 may be able to access clinician interface 26 via a clinician programmer, clinic workstation, tablet computer, webpage, or a consumer electronic device (e.g., a cellular telephone). In this manner, clinician module 16 may be provided by a clinic server or other remote computing device and clinician 15 may update therapy instructions and receive patient 12 information at any location.

In some examples, clinician module 16 may also include a memory for storing data. For example, in some examples, the memory may store information related to patient 12, e.g., health information, sensed physiological parameters, historical condition data, prescription information, or other information related to clinician 15 such as identification information. In some examples, the memory may also store other data that may be useful in managing the medical condition of patient 12. The memory can include any suitable type of memory, such as RAM, ROM, PROM, EPROM, EEPROM, flash memory, a hard disk, a CD-ROM, a floppy disk, a cassette, magnetic media, optical media, or other computer readable media.

Clinician interface 26 can be any user interface suitable for interaction with clinician 15. For example, clinician interface 26 may include a display and one or more input buttons that allow another component of system 10 to receive input from clinician 15. Alternatively or additionally, clinician interface 26 may utilize a touch screen display. The screen may be a LCD, dot matrix display, OLED display, touch screen, or any other device capable of delivering and/or accepting information. For visible indications of information, a display screen may suffice. For audible and/or tactile indications of information, clinician interface 26 may further include one or more audio speakers, voice synthesizer chips, piezoelectric buzzers, or the like.

Input buttons for clinician interface 26 may include a touch pad, increase and decrease buttons, emergency shut off button, and other buttons that may control or modify a therapy delivered to patient 12, as well as other buttons for inputting information into clinician module 16. A processor of system 10 may control clinician interface 26, retrieve data stored in a memory of system 10, store data within a memory of system 10, and/or transmit data from clinician module 16 to another module of system 10.

Therapy module 18 may include any components and configuration suitable for storing the therapy instructions that associates patient conditions with the one or more therapy regimens used to treat patient 12, and providing remote access to the stored therapy instructions. For example, in some examples, therapy module 18 includes a memory (i.e., one or more memories) for storing the preset patient conditions detectable based on a physiological parameter sensed by sensor 22. These patient conditions may be ranges for specific physiological parameters sensed by sensor 22 or some other function of sensor 22 output. The memory may also store a plurality of therapy regimens of the therapy instructions. Each therapy regimen may be a specific set of medications, doses, and delivery times.

In some examples, the plurality of stored therapy regimens may not merely include predetermined prescriptions that are each associated with a condition. Instead of or in addition to a predefined prescription that is associated with a respective condition, the plurality of stored therapy regimens may be defined by an equation or algorithm that indicates a prescription that is a function of the detected condition. For example, the dosage, intake times, and/or medications of each prescription may be generated based on the detected condition, e.g., the contingent prescriptions may be one prescription that varies based on the condition, and the stored equation or algorithm. In this fashion, clinician 15 may not need to create a large table of condition-therapy regimens associated with each condition.

In one example, an algorithm for selecting a therapy regimen includes monitoring a physiological parameter of patient 12 and determining whether the patient condition has been stagnant for a particular time range (e.g., the past day, days or week). If the patient condition is stagnant (e.g., the determined patient condition has not changed), the algorithm may include modifying the current therapy regimen in a manner that may help improve the patient condition (e.g., change the current patient condition). The algorithm may implement rules for modifying the current therapy regimen, such as increasing a dosage of a particular medication or adding a medication to the therapy regimen. The rules may be, for example, determined by clinician 15 in some examples. As an example of this type of algorithm, therapy module 18 can automatically monitor a physiological parameter of the patient, and determine, based on past physiological parameter data, whether the patient condition is improving (e.g., approaching a normal pulmonary pressure over time). If the physiological parameter indicates the patient condition is not improving, therapy module 18 can implement a therapy regimen that may help improve the patient condition (e.g., by selecting the therapy regimen from a plurality of stored therapy regimens or by adjusting the current therapy regimen based on a set of stored rules).

In another example, rather than implementing an algorithm to vary a therapy regimen based on historical patient condition data (e.g., a pattern in the patient condition over time), therapy module 18 can adjust a therapy regimen based on therapy regimens associated with a detected patient condition pattern. For example, clinician 15 can define a patient condition as including a time component (e.g., a high pressure detected for a certain number of hours or days), and associate a therapy regimen with the patient condition. In this way, therapy module 18 can select a therapy regimen based on a patient condition determined over the course of one or more days, rather than an instantaneous patient condition.

In addition to a memory, therapy module 18 may include a processor that can execute therapy instructions by automatically selecting a therapy regimen based on a patient condition detected based on a physiological parameter sensed by sensor 22. In some examples, therapy module 18 may include one or more databases for storing therapy instructions, historical condition data, therapy regimens, or any other information used by system 10 to monitor and treat patient 12.

In some examples, patient module 14, clinician module 16, and algorithm module 18 may be located remotely from one another. For example, in some examples, one or more of patient module 14, clinician module 16, and algorithm module 18 may be provided in different locations. As one example, patient module 14 may be located in the home of patient 12, clinician module 16 may be located in a medical care facility, e.g., a clinic or a hospital, and therapy module 18 may be located in an external server at a separate server facility. In another example, therapy module 18 and patient module 14 may be located in a device within the home of patient 12, while, in other examples, therapy module 18 and clinician module 16 may be located in the same medical care facility. In still other examples, two or more of the modules of system 10 may even be located within the same device (e.g., a patient programmer carried by patient 12). As these examples illustrate, patient module 14, clinician module 16, and therapy module 18 may be located in any configuration that facilitates the monitoring and treatment of patient 12.

Patient module 14, clinician module 16, and therapy module 18 may communicate with one another via network 20 when located remote from one another. In some examples, network 20 includes one or more of a local area network (LAN), wide area network (WAN), public switched telephone network (PSTN), or cellular telephone network. One or more components of patient module 14, clinician module 16, and therapy module 18 may be configured to connect to network 20 in order to transmit and receive information between modules 14, 16, and 18.

In general, clinician module 16 receives input from clinician 15 to define the therapy instructions used by therapy module 18 to select the appropriate therapy regimen, e.g., contingent medication prescription. In some examples, the therapy instructions may include additional instructions to monitor multiple conditions of patient 12. For example, clinician 15 may define other instructions, or algorithms that therapy module 18 may use to automatically monitor patient 12. That is, clinician 15 may initially provide input to define each of the instructions, or algorithms, that allow therapy module 18 to subsequently monitor and treat the patient 12 with minimal interaction from clinician 15 otherwise required.

Sensor 22 of patient module 14 may sense a physiological parameter of patient 12 that can be used to detect a condition of patient 12, which is then used to determine a therapy regimen for patient 12. The output of sensor 22 can be an electrical signal that is directly representative of the physiological parameter, such as a pressure or impedance. Therapy module 18 (or another module of system 10) may detect a condition of patient 12 when the physiological parameter correlates with the condition, e.g., as indicated by stored data that defines a condition. For example, clinician 15 may set a physiological parameter value range for each condition, and each condition is then detected when sensor 22 senses a physiological parameter value that correlates to that condition. In other examples, one or more sets of therapy instructions may be used to correlate sensed parameters to each of the conditions. As described with respect to FIG. 2, the therapy instructions may include, for example, a set of instructions for detecting a specific pressure range and a set of instructions for detecting a specific change in pressure. In other examples, sensor 22 may implement a portion of the therapy instructions so that sensor 22 identifies the condition based on the sensed physiological parameters.

As described herein, each condition may be associated with a therapy regimen designed to treat patient 12. Because sensor 22 may sense different types of physiological parameters in some examples, each condition may be varying degrees of one type of physiological parameter and varying degrees of another type of a different physiological parameter. For example, each condition may relate to different blood pressure states, different trans-thoracic impedances, or even different combinations of these two measurements.

In one example of sensor 22, as discussed in further detail with respect to FIGS. 2 and 3, may be configured and positioned relative to patient 12 to sense right ventricular pressure (i.e., one type of a physiological parameter) of patient 12. In some examples, right ventricular pressure may be used in place of pulmonary artery pressure because the two pressures can be roughly equivalent when the pulmonary valve is open during right ventricular contractions. As discussed in further detail below, pulmonary artery pressure may be used as an indicator of the progression of congestive heart failure of patient 12. Therefore, therapy module 18 may detect a pulmonary artery pressure severity condition based on the sensed right ventricular pressure from sensor 22. For example, each condition may relate to a pressure range defined by the therapy instructions (e.g., very low pressure, low pressure, normal pressure, high pressure, and very high pressure). Pulmonary artery pressure can be used to define five different conditions for patient 12 in this example. Each condition may also indicate a certain risk for HF, e.g., conditions of higher pulmonary pressure indicates more thoracic fluid volume and/or more stress on the right ventricle of the heart.

Sensor 22 may sense physiological parameters indicative of the condition continuously, periodically, or in response to any event and transmit an indication of the sensed parameters to clinician module 16 or therapy module 18 as required for management of the medical condition (e.g., HF). Although sensor 22 may sense a physiological parameter that is indicative of the condition of patient 12, the actual detection of the condition by system 10 may not occur at sensor 22. For example, patient module 14 may include a processor that receives the output, e.g., a physiological parameter, from sensor 22 and determines, based on the sensor output, whether the patient condition is detected. As another example, patient module 14 may transmit the sensed physiological parameter to therapy module 18, which may then detect the patient condition. Therapy module 18 may then correlate the sensed physiological parameter to one of the conditions associated with the therapy instructions. In other examples, clinician module 16 may detect the patient condition based on the output from sensor 22.

In any case, sensor 22 may directly or indirectly detect the specific condition. When matching the sensed physiological parameter to one of the conditions, the therapy instructions may use a condition identifier having addition instructions or equations for identifying the condition from the physiological parameter. In one example, the conditions identifiers may be a pressure range check instruction, a pressure change detection instruction, or a patient pressure status instruction.

In some examples, clinician module 16 displays medical information of patient 12 via clinician interface 26. Clinician 15 may review the medical information displayed on clinician interface 26 and provide input that defines the therapy instructions, e.g., the conditions or condition identifiers, used to monitor the progression or regression of patient 12. In addition, clinician 15 may provide input to clinician interface 26 defining a plurality of therapy regimens that may be transmitted to patient module 14 for presentation to patient 12. The therapy regimens may be contingent prescriptions for a certain therapy. In other words, clinician 15 may load any number of therapy regimens into the therapy instructions such that each therapy regimen is contingent upon an associated condition being detected from patient 12.

In one example, the therapy regimens may be contingent medication prescriptions that instruct patient 12 to take certain medication, the appropriate dose of the medication, and the time for taking each medication. In some examples, therapy regimens may include instructions for patient 12 to assume certain postures, assume certain positions or undertake certain activities, or even to contact another healthcare professional. In some examples, the therapy regimens may include instructions for implementation by patient 12 for activating, deactivating, or otherwise modifying one or more medical devices used to manage the detected condition. In other examples, the therapy regimens may include instructions that command one or more components of patient module 14 to automatically titrate a therapy, e.g., electrical stimulation therapy or drug delivery, for treating the medical condition of patient 12. It is noted that the therapy regimens included in the therapy instructions defined by clinician 15 may included any of these types of therapies at the same time. For example, the therapy instructions for patient 12 may include both therapy regimens of medications and adjustments to medical devices. Other types of therapy regimens are contemplated.

In some examples, clinician module 16 receives medical information related to patient 12 from one or more components of patient module 14. For example, patient module 14 may store medical information related to patient 12, such as medical history information of patient 12, historical or real-time physiological parameters (e.g., sensed data by sensor 22) of patient 12, detected conditions, feedback from patient 12 related to previously implemented therapy regimens, and the like, and transmit the medical information to clinician module 16 via network 20. Upon receiving the medical information, clinician module 26 may display the information via clinician interface 26 such that clinician 15 can review the information. Clinician 15 may review this information, or portions of this information, and create a therapy plan specific to patient 12. In other examples, clinician module 16 may provide medical information from other patients. Clinician 15 may then use this information from other patients to identify those therapy regimens effective in treating conditions similar to the ones of patient 12. This other patient information may be from patients treated by clinician 15, a clinic in which clinician 15 practices medicine, or even remote patients with information included in an accessible database.

Based upon reviewing the medical information of patient 12, clinician 15 may provide input via clinician interface 26 defining the therapy instructions. This input may specify the parameters of condition identifier algorithms, specific conditions, or even the therapy regimens for each of the conditions detectable based on a physiological parameter sensed by sensor 22. As described above, the condition identifiers may define how to relate sensed physiological parameters to one of the conditions, e.g., by associating specific physiological parameter values with a specific patient condition. The input from clinician 15 may also define associations between each of the conditions and a therapy regimen for patient 12 when the condition is detected. In other words, the input provided by clinician 15 may indicate a correlation between particular conditions of patient 12 and particular treatment regimens that, according to clinician 15, may most effectively treat the detected condition of patient 12.

Clinician module 16 may subsequently transmit the therapy instructions received via clinician interface 26 to therapy module 18 so that therapy module 18 may automatically select the therapy regimen associated with patient condition detected based on the physiological parameter sensed by sensor 22. In some examples, clinician module 16 may only transmit changes in the therapy instructions to therapy module 18. In other words, clinician module 16 may keep a copy of the therapy instructions stored at therapy module 18 and look for changes made to the therapy instructions by clinician 15. Clinician module 16 may then only transmit the recognized changes to the therapy instructions as an update to the previously existing therapy instructions.

Upon acquiring the therapy instructions from clinician module 16, therapy module 18 may be capable of monitoring and treating patient 12 by automatically selecting a therapy regimen based on a detected patient condition. For example, a processor of therapy module 18 may analyze physiological parameters received from sensor 22 and determine, based on the analysis of one or more physiological parameters with a condition identifier, whether the patient condition has been detected. Therapy module 18 may then automatically select a therapy regimen associated with the detected condition and transmit the selected therapy regimen to patient module 14. Therapy module 18 may perform the automatic selection at any time predefined by clinician 15, as requested by patient 12, or otherwise required by circumstances surrounding patient 12. In this manner, system 10 may effectively treat patient 12 in more responsive manner than possible with manual observation and therapy updates. In other examples, patient module 14 or clinician module 16 may automatically select the therapy regimen based on the detected condition. Any module of system 10 may select the therapy regimen according to therapy instructions.

Therapy module 18 may transmit the selected therapy regimen to patient module 14 via network 20. In some examples, patient module 14 displays the therapy regimen on patient interface 24 for review by patient 12. The therapy regimen may include written instructions instructing patient 12 to modify an aspect of one or more therapies designed to treat or minimize the medical condition of patient 12. For example, the therapy regimen may include instructions for patient 12 to alter a dosage, frequency, time, etc. of taking a medication that is used to treat the medical condition of patient 12. In this example, the therapy regimen may include a contingent medication prescription. In some examples, the therapy regimen set may instruct patient 12 to contact clinician 15 or another clinician based on the detected condition of patient 12. In examples in which patient module 14 includes a therapy delivery component or device, e.g., an implantable medical device (IMD) or external device that delivers therapy to patient 12, the therapy regimen may include an adjustment to the therapy program implemented by the device. Patient 12 may need to manually adjust one of the parameters of the therapy program or patient module 14 may automatically upload the updated therapy program to the device. Patient 12 may still be notified of such an automatic update to the therapy program.

Many examples herein, such as the examples illustrated in FIGS. 2 and 3, are described with respect to patient 12 suffering from congestive heart failure (HF) and integrated patient care system 30 (of FIG. 2) configured to monitor and treat the congestive heart failure of patient 12. However, as discussed, in other examples, patient 12 may suffer from another medical problems or circumstances that may benefit from an integrated patient care system configured to monitor and treat patient 12.

FIG. 2 is a schematic illustration of integrated patient care system 30, which is configured to monitor and treat congestive heart failure of patient 12. System 30 of FIG. 2 may be substantially similar to system 10 of FIG. 1. As illustrated in the example of FIG. 2, system 30 generally includes patient module 32, clinician module 34, and therapy module 36, in addition to network 38 via which patient module 32, clinician module 34, and therapy module 36 communicate with one another. In the example illustrated in FIG. 2, for monitoring and providing therapy for congestive heart failure, patient module 32 includes sensor 40, patient interface 42, and ancillary data 46. Clinician module 34 includes clinician interface 44, condition module 52, condition history module 54, and therapy regimens module 56. Therapy module 36 includes therapy instructions module 57, pressure range check (PRC) instruction module 58 and pressure change detection (PCD) instruction module 60.

Patient module 32 may be substantially similar to patient module 14 (FIG. 1) and may be configured as a component of integrated patient care system 30. Patient module 32 includes patient interface 42 that includes a display to present information to patient 12 and one or more devices that receive input from patient 12. Patient module 32 also includes sensor 40 that is configured to sense right ventricular pressure of patient 12, which may be used to monitor the congestive heart failure of patient 12. Sensor 40 of FIG. 2 includes pressure sensor 48 and data storage 50. In other examples, sensor 40 may include a separate processor or other components used to detect a condition of patient 12.

In the example of FIG. 2, pressure sensor 48 is configured and positioned within patient 12 to sense pressure in the pulmonary artery of patient 12, which may be used to monitoring the severity, or degree, of congestive heart failure of patient 12. Sensor 40 includes data storage module 50 which may be a memory that stores data related to the sensed pressure parameter from pressure sensor 48. Data storage 50 may include the raw output from pressure sensor 48, the calibrated pressure that was sensed, or even the condition detected from the sensed pressure in some examples. Data storage 50 may also store a time stamp of when the pressure was sensed and other operational data related to pressure sensor 48. Patient module 32 also includes ancillary data module 46 that may sense and/or store ancillary data of patient 12. Ancillary data may be any data indicative of the general health or information of patient 12. For example, in some examples, ancillary data may include data related to the vital signs of patient 12, e.g., body temperature, respiration rate, heart rate, and blood pressure of patient 12. In other examples, ancillary data 46 may store information regarding the activity of patient 12, postures of patient 12, or any other data. Therefore, ancillary data 46 may include a memory for storing the ancillary data and/or one or more sensors that generate the ancillary data.

Patient interface 42 may be substantially similar to patient interface 24 (FIG. 1), and may be useful for displaying or presenting information to patient 12. For example, patient interface 42 may present one or more therapy regimens selected by therapy module 36, instructions with which patient 12 may implement the selected therapy regimen, e.g., to take a particular dosage of medication at a particular time of day for managing the congestive heart failure of patient 12. In other examples, patient interface 42 may be used to receive feedback from patient 12 regarding any aspects of the distributed therapy regimen or associated features of system 30. For example, patient interface 42 may prompt patient 12 to provide feedback indicative of one or more side effects related to the selected therapy regimen, a rating related to the effectiveness of the selected therapy regimen, health history information that may be useful to clinician 15 for managing the congestive heart failure of patient 12, or any other information related to the treatment of patient 12.

In the example shown in FIG. 2, pressure sensor 48 senses a physiological parameter used to detect a condition of patient 12. In the example of FIG. 2, the sensed physiological parameter is pulmonary artery pressure and the condition is a level of the pulmonary artery pressure. Although the examples described herein relate to detecting pressure states, e.g., which are conditions of patient 12 in this example, from sensed pulmonary artery pressures of patient 12, patient module 32 may detect pulmonary pressure states from other sensed physiological parameters or different conditions from one or more physiological parameters in some examples. In other examples, patient module 32 may detect several different types of conditions at the same time. In this example, patient module 32 may detect a posture condition and a pulmonary artery pressure to provide a more complete indication of patient 12 symptoms. In any case, sensor 40 may detect a condition of patient 12 for selecting a therapy regimen previously prescribed by clinician 15 contingent upon the detection of the condition.

A pulmonary artery pressure level may be an appropriate condition to be used an indicator of the status of the congestive heart failure of patient 12. Because congestive heart failure may result in accumulation of fluid in the lungs of patient 12, e.g., pulmonary edema, pulmonary artery pressure may increase when heart failure becomes more severe. Progression of congestive heart failure, therefore, may be indicated by increasing pulmonary artery pressures. Since pulmonary artery diastolic (PAD) pressure may be correlated to left ventricular filling pressure, an elevated PAD pressure may indicate a high level of fluid within the lungs of patient 12 and potential cardiac problems. For example, an elevated PAD pressure may indicate excess stress on the right ventricle and potential right ventricle enlargement. In addition, an elevated PAD pressure may indicate that the left ventricle may become enlarged such that the expanded cardiac muscle is limited in its ability to maintain sufficient systemic blood flow levels. Once the heart is unable to maintain appropriate systemic blood flow, tissues and organs may lose their ability to obtain oxygen, among other chemical transport needs.

Pressure sensor 48 or, more generally, sensor 40, may measure the pulmonary artery pressure of patient 12 in any suitable manner. In some examples described herein, sensor 40 is implanted within the right ventricle of patient 12 (e.g., as illustrated in FIG. 3) to measure the right ventricular pressure of patient 12. The right ventricular pressure may subsequently be used to derive an estimated pulmonary artery diastolic (ePAD) pressure for patient 12. In other words, sensor 40 may still detect the pulmonary artery pressure condition of patient 12. The ePAD pressure generally refers to the measure of right ventricular pressure at the time the change in the pressure signal over time (dp/dt) is at a maximum. In some examples, as discussed in further detail in commonly-assigned U.S. Patent Application Publication No. 2009/0299198 by Carney et al., filed on May 20, 2008, entitled “ESTIMATING PULMONARY ARTERY DIASTOLIC PRESSURE,” and herein incorporated by reference in its entirety, sensor 40 may determine an approximate time at which the pulmonary artery valve of patient 12 opens based on the right ventricular pressure in order to estimate the pulmonary artery diastolic pressure. In other examples, sensor 40 may determine ePAD pressure values for patient 12 in another suitable manner. For example, sensor 40 may be an ultrasound sensor implanted on the pulmonary artery to monitor flow and estimate the diastolic and even systolic pressures within the pulmonary artery.

An increase in ePAD pressure values may indicate that the congestive heart failure of patient 12 has worsened. For example, as discussed above, an increase in fluid in the lungs of patient 12 may be indicative of increased severity of the congestive heart failure, and may accordingly cause an increase in ePAD pressure values. Consequently, an increase in ePAD pressure values may be indicative of increased severity of the congestive heart failure. Conversely, a decrease in ePAD pressure values may signify the congestive heart failure condition of patient 12 has improved, e.g., a currently or previously implemented therapy regimen has reduced the amount of fluid within patient 12 lungs and/or dilated the blood vessels of patient 12.

In other examples, sensor 40 may be used to monitor the severity of heart failure by measuring a physiological parameter other than pulmonary pressures. For example, sensor 40 may include one or more electrodes used to measure a trans-thoracic impedance (which may also be referred to as intrathoracic impedance in some cases) of patient 12. When there is more fluid within patient 12, e.g., indicating pulmonary edema, the measured, or sensed, trans-thoracic impedance may decrease. In some cases, this trans-thoracic impedance may be used as a substitute for pulmonary artery pressures. The trans-thoracic impedance may be sensed by measuring the impedance of an electrical path between two electrodes, or combinations of multiple electrodes, at different locations with respect to the chest of patient 12. The electrodes may have different configurations to measure the impedance.

As examples of electrode configurations, both electrodes may be implanted within patient 12, both electrodes may be attached to the external skin surface of patient 12, or one electrode may be implanted and one electrode may be external. In a specific example, the electrodes already implanted within the patient when patient 12 has an implanted pacemaker, cardioverter and/or defibrillator or another medical device can be used to determine trans-thoracic impedance of patient 12. For example, a coil electrode within the heart and the housing electrode of the implantable medical device may be used an implanted electrodes to measure the trans-thoracic impedance. In this manner, patient module 32 may communicate with the implanted medical device in some examples to detect a patient condition. In another example, patient 12 may wear surface electrodes attached to the chest and electrically coupled to an external medical device that measures the impedance between the surface electrodes. In other examples, sensor 40 may be any sensor capable of detecting one or more conditions indicative of heart failure severity.

Data storage module 50 of sensor 40 may include one or more memory components that may, in some examples, store pressure measurement values sensed by pressure sensor 48. The memory can include any suitable type of memory, such as RAM, ROM, PROM, EPROM, EEPROM, flash memory, a hard disk, a CD-ROM, a floppy disk, a cassette, magnetic media, optical media, or other computer readable media. In some examples, patient module 32, clinician module 34, or therapy module 36 may access the stored data in data storage module 50 to detect the patient condition. In other examples, data storage 50 may only be used as temporary storage that is periodically transmitted to therapy module 36 via network 38.

Clinician module 34 may be substantially similar to clinician module 16 (FIG. 1) and may be configured as a component of integrated patient care system 30. Clinician module 34 includes clinician interface 44 for displaying information to and receiving input from clinician 15 and historical condition information in condition history 54. Condition history 54 may store previously collected physiological parameters and/or detected conditions of the pulmonary artery pressure of patient 12. For example, condition history 54 may include a memory that stores data for illustrating previous trends in the pulmonary artery pressure of patient 12. The memory can include any suitable type of memory, such as RAM, ROM, PROM, EPROM, EEPROM, flash memory, a hard disk, a CD-ROM, a floppy disk, a cassette, magnetic media, optical media, or other computer readable media. In addition, clinician module 34 includes condition module 52 and therapy regimen module 56. Together, condition module 52 and therapy regimen module 56 may provide therapy instructions 57 stored by therapy module 36. Therapy module 36 may use therapy instructions 57 to select the appropriate therapy regimen based on the detected condition. In other words, in some examples, clinician 15 may associate one or more conditions 52 with a therapy regimen of therapy regimens 56. This association may be transmitted to therapy module 36 and stored as therapy instructions 57.

The criteria with which each condition is detected from the sensed physiological parameters may also be determined by clinician 15. These criteria may also be referred to as condition identifiers because they identify how each condition is detected. In the example of FIG. 2, clinician 15 may select from three different criteria (also referred to as condition identifiers) for determining the condition of patient 12: pressure range, pressure change, and both pressure range and pressure change. Pressure range check (PRC) instruction module 58 of therapy module 36 associates each of a plurality of patient conditions with a range of values for the sensed physiological pressure. Pressure change detection (PCD) instruction module 60 of therapy module 36 associates each of a plurality of patient conditions with a threshold value for a change in pulmonary artery pressure. The different parameters (e.g., the range of values for a sensed physiological parameter associated with a respective condition or a threshold value for PCD associated with a respective condition) of each condition identifier may be stored as conditions 52 of clinician module 34.

Therapy instructions 57 may include PRC module 58 and PCD module 60 in other examples, and therapy instructions 57 may define parameters of each module 58 and 60. In other examples, therapy instructions 57 may include other modules that perform other functions defined by therapy instructions 57. For example, a condition state module may use the output from one or both of modules 58 and 60 to detect the condition from sensed physiological parameters. In another example, a patient therapy module may contain the associations between each condition and therapy regimens.

In some examples, clinician 15 may select which one of the condition identifiers (e.g., pressure range or pressure change) should be used to detect the patient conditions stored in therapy instructions 57. In other examples, clinician 15 may require that conditions are only detected when two condition identifiers (e.g., pressure range check and pressure change detection) indicate conditions associated with the same therapy regimen. In this manner, therapy module 36 may confirm the patient condition before releasing a contingent prescription from therapy instructions 57.

Clinician interface 44 may be substantially similar to clinician interface 26 (FIG. 1), and may display information to clinician 15 and receive input related to generating or updating therapy instructions 57. Clinician interface 44 may include a display that presents historical conditions from condition history 54, conditions to be detected from patient 12, and therapy regimens. In turn, clinician interface 44 may receive input from clinician 15 that sets the parameters of conditions 52, generates contingent prescriptions as therapy regimens 56, or other instructions related to the monitoring and treatment of patient 12. Clinician module 34 may then transmit updated therapy instructions 57 to therapy module 36 when clinician 15 is finished.

As described herein, therapy module 36 may transmit the parameters (e.g., threshold values or other values used to identify a patient condition) of one or more condition identifiers to clinician module 34 for review, and, in some cases, modification. In the example shown in FIG. 2, the condition identifiers are stored as PRC instruction module 58 and PCD instruction module 60. For each condition identifier 58, 60, clinician interface 44 may present the parameters to clinician 15 and clinician 15 may review how each parameter of the condition identifier is correlating to the historical condition data from sensor 40. For example, clinician interface 44 may present parameters of the PRC condition identifiers for identifying conditions, where the parameters include physiological parameters associated with a respective patient condition. Physiological parameter data may be presented in conjunction with the condition identifier parameters, and clinician 15 may adjust one or more condition identifier parameters to adjust when the physiological parameters indicate each condition is detected. This relationship between condition identifier parameters and physiological parameters of historical conditions is further illustrated below in FIG. 6.

In other examples of FIG. 2, therapy module 36 may use a different technique other than stored therapy instructions 57 to detect conditions and select a therapy regimen based on the detection. For example, in some examples, the physiological parameters, e.g., pulmonary pressure, may be transmitted from sensor 40 and patient module 32 to therapy module 36 via network 38. Therapy module 36 may determine the patient condition indicated by the sensed physiological parameters based on the received physiological parameters and condition identifiers 58 and 60. For example, therapy module 36 can determine a pressure state of patient 12 indicated by the sensed physiological parameters by comparing the sensed physiological parameters to the range of the pressure range parameters stored as PRC 58 and a detected pressure change value stored as PCD 60. Therapy module 36 can then select the appropriate therapy regimen based on the detected pressure state. In this manner, therapy module 36 may operate differently than a single look-up table or formula because multiple criteria may be used to determine the patient condition. Of course, clinician 15 may be able to configure each parameter of the modules used in this method to customize the detected conditions and therapy regimens for patient 12.

FIG. 3 illustrates a portion of a patient module 34 that includes sensor 40 implanted within right ventricle 70 of heart 66 in patient 12. As shown in the example of FIG. 3, system 65 includes sensor 40, a wireless pressure sensor attached to the chamber wall within right ventricle 70. Sensor 40 may be implanted with an intravenous lead and secured at a location within right ventricle 70 that does not interfere with normal contractions of right ventricle 70. In examples in which sensor 40 includes a wireless sensor 40, sensor 40 may include a power source, processor, telemetry module, and anything else required for sensor 40 to function. In this manner, programmer 72 may receive sensed pressures, e.g., physiological parameters, from sensor 40.

Sensor 40 may be configured to sense right ventricular pressure of patient 12 in the example of FIG. 3. As described herein, right ventricular pressure may be used to monitor the congestive heart failure condition of patient 12. Right ventricular pressure may be used to estimate the pulmonary artery diastolic pressure, and, accordingly, system 65 may detect the pressure condition of the pulmonary vasculature based on the right ventricular pressure. Other configurations and locations of sensor 40 within patient 12 may also be used. For example, in other examples, sensor 40 may be located on a lead that passes through right atrium 68 and also resides within right ventricle 70. For example, sensor 40 may be carried on a lead used by a pacemaker, a cardiac resynchronization therapy (CRT) device, cardioverter and/or defibrillator.

Programmer 72 may be configured to communicate with sensor 40, e.g., via wireless telemetry. Programmer 72 may be part of the patient module 32 used to monitor patient 12. Programmer 72 may, in some examples, transmit the pressures sensed by sensor 40 to therapy module 36, which may select a therapy regimen based on the patient condition detected based on the pressure sensed by sensor 40.



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stats Patent Info
Application #
US 20120108984 A1
Publish Date
05/03/2012
Document #
12915992
File Date
10/29/2010
USPTO Class
600485
Other USPTO Classes
705/2
International Class
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Drawings
22


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Surgery   Diagnostic Testing   Cardiovascular   Measuring Pressure In Heart Or Blood Vessel